---
base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
tags:
- generated_from_keras_callback
model-index:
- name: Roberta-base-financial-sentiment-analysis
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# Roberta-base-financial-sentiment-analysis

This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0013
- Train Accuracy: 1.0
- Validation Loss: 0.2910
- Validation Accuracy: 0.9431
- Epoch: 9

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 3030, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.4682     | 0.8080         | 0.3497          | 0.8687              | 0     |
| 0.1674     | 0.9504         | 0.2655          | 0.9064              | 1     |
| 0.1139     | 0.9681         | 0.2639          | 0.9189              | 2     |
| 0.0847     | 0.9723         | 0.2259          | 0.9334              | 3     |
| 0.0454     | 0.9876         | 0.2156          | 0.9440              | 4     |
| 0.0262     | 0.9897         | 0.2593          | 0.9344              | 5     |
| 0.0136     | 0.9963         | 0.3786          | 0.9170              | 6     |
| 0.0043     | 0.9988         | 0.2589          | 0.9488              | 7     |
| 0.0042     | 0.9988         | 0.2866          | 0.9450              | 8     |
| 0.0013     | 1.0            | 0.2910          | 0.9431              | 9     |


### Framework versions

- Transformers 4.32.0
- TensorFlow 2.12.0
- Datasets 2.14.4
- Tokenizers 0.13.3